The present invention relates to clothing recognition from video.
Clothing recognition is an advanced and emerging multimedia application, which may benefit customer profile analysis, context-aided people identification, and computer aided fashion design. Although this problem attracts increasing research interests in recent years, a real-time clothing recognition system, especially for surveillance videos, remains challenging, primarily due to two reasons. First, such a system involves a series of difficult sub-problems including face detection and tracking, human figure or clothing segmentation, and effective clothing representations. Second, the differences among various clothing categories are inherently subtle and sometimes even vague for human, thus considerable computations may be required to discern them.
In digital analysis of clothing images, conventional systems typically segmented clothes as foreground objects assuming certain foreground seeds or regions of interests provided by users, or the same clothes appearing in different backgrounds. In other works, rough clothing analysis was employed as contexts to help people identification. High-level modeling of clothes based on And-Or graphs also have been tried. Responsive and smart mirrors have been used to retrieve similar clothing styles for fashion recommendation in a fitting room.